class_docstr: KNRM model.
  
  Examples:
      >>> model = KNRM()
      >>> model.params['embedding_input_dim'] =  10000
      >>> model.params['embedding_output_dim'] =  10
      >>> model.params['embedding_trainable'] = True
      >>> model.params['kernel_num'] = 11
      >>> model.params['sigma'] = 0.1
      >>> model.params['exact_sigma'] = 0.001
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
docstr: Get default parameters.
docstr_tok: ["Get","default","parameters","."]
code: def get_default_params(cls):
      """Get default parameters."""
      params = super().get_default_params(with_embedding=True)
      params.add(
          Param(
              name="kernel_num",
              value=11,
              hyper_space=hyper_spaces.quniform(low=5, high=20),
              desc="The number of RBF kernels.",
          )
      )
      params.add(
          Param(
              name="sigma",
              value=0.1,
              hyper_space=hyper_spaces.quniform(
                  low=0.01, high=0.2, q=0.01
              ),
              desc="The `sigma` defines the kernel width.",
          )
      )
      params.add(
          Param(
              name="exact_sigma",
              value=0.001,
              desc="The `exact_sigma` denotes the `sigma` "
              "for exact match.",
          )
      )
      return params
  
file_path: MatchZoo/matchzoo/models/knrm.py
imports: import keras
  import tensorflow
  from matchzoo.engine.base_model import BaseModel
  from matchzoo.engine.param import Param
  from matchzoo.engine import hyper_spaces
label_desc: Use image node_id 1 for calling the KNRM obj's underlying member method code with example usage: obj.get_default_params(cls) and returns: params